Edward Elson Kosasih

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Alexandra BrintrupUniversity of CambridgeVerified email at cam.ac.uk
A. CalinescuDepartment of Computer Science, University of Oxford; The Alan Turing InstituteVerified email at cs.ox.ac.uk
Angira SharmaUniversity of OxfordVerified email at cs.ox.ac.uk
Zhang JieUniversity of BristolVerified email at bristol.ac.uk
Ajmal AzizUniversity of CambridgeVerified email at cam.ac.uk
Fabrizio MargaroliAssistant Professor, Rome La Sapienza UniversityVerified email at roma1.infn.it
Güven DemirelReader, School of Business and Management, Queen Mary University of LondonVerified email at qmul.ac.uk
Kelvin IdanwekhaiUniversity of North Carolina at Chapel HillVerified email at unc.edu
Kamil TagowskiWroclaw Univeristy of Science and TechnologyVerified email at pwr.edu.pl
Arian JamasbUniversity of Cambridge, Prescient DesignVerified email at cam.ac.uk
Yuqian LuSenior Lecturer, University of AucklandVerified email at auckland.ac.nz
George BaryannisSubject Area Leader (Computing and Information Systems), University of HuddersfieldVerified email at hud.ac.uk
Emmanuel PapadakisLecturer, Department of Computer Science, University of HuddersfieldVerified email at hud.ac.uk
Ryan-Rhys GriffithsMeta ResearchVerified email at cam.ac.uk
Piotr BielakWrocław University of Science and TechnologyVerified email at pwr.edu.pl
Benedict Aaron TjandraUniversity of CambridgeVerified email at cantab.ac.uk
Nils BrockmannPostgraduate Student, University of CambridgeVerified email at cam.ac.uk
Ge ZhengResearch Associate, Institute of Manufacturing, Department of Engineering, Cambridge UniversityVerified email at cam.ac.uk
Rucha Bhalchandra JoshiStudent, National Institute of Science Education and ResearchVerified email at niser.ac.in
Janamejaya ChannegowdaTechnical lead at L&T Technology ServicesVerified email at ltts.com

Edward Elson Kosasih

University of Cambridge

Verified email at cantab.ac.uk - Homepage

machine learning operations research network science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Digital twins: State of the art theory and practice, challenges, and open research questions A Sharma, E Kosasih, J Zhang, A Brintrup, A Calinescu Journal of Industrial Information Integration 30, 100383, 2022	227	2022
A machine learning approach for predicting hidden links in supply chain with graph neural networks EE Kosasih, A Brintrup International Journal of Production Research 60 (17), 5380-5393, 2022	102	2022
Towards knowledge graph reasoning for supply chain risk management using graph neural networks EE Kosasih, F Margaroli, S Gelli, A Aziz, N Wildgoose, A Brintrup International Journal of Production Research, 1-17, 2022	35	2022
Dynamic inventory replenishment strategy for aerospace manufacturing supply chain: combining reinforcement learning and multi-agent simulation H Wang, J Tao, T Peng, A Brintrup, EE Kosasih, Y Lu, R Tang, L Hu International Journal of Production Research 60 (13), 4117-4136, 2022	19	2022
Reinforcement learning provides a flexible approach for realistic supply chain safety stock optimisation EE Kosasih, A Brintrup IFAC-PapersOnLine 55 (10), 1539-1544, 2022	15	2022
Supply chain digital twin framework design: an approach of supply chain operations reference model and system of systems J Zhang, A Brintrup, A Calinescu, E Kosasih, A Sharma arXiv preprint arXiv:2107.09485, 2021	15	2021
Data considerations in graph representation learning for supply chain networks A Aziz, EE Kosasih, RR Griffiths, A Brintrup arXiv preprint arXiv:2107.10609, 2021	12	2021
Digital supply chain surveillance: concepts, challenges, and frameworks A Brintrup, EE Kosasih, BL MacCarthy, G Demirel The Digital Supply Chain, 379-396, 2022	10	2022
On graph neural network ensembles for large-scale molecular property prediction EE Kosasih, J Cabezas, X Sumba, P Bielak, K Tagowski, K Idanwekhai, ... arXiv preprint arXiv:2106.15529, 2021	8	2021
Supply chain link prediction on uncertain knowledge graph N Brockmann, E Elson Kosasih, A Brintrup ACM SIGKDD Explorations Newsletter 24 (2), 124-130, 2022	7	2022
A review of explainable artificial intelligence in supply chain management using neurosymbolic approaches EE Kosasih, E Papadakis, G Baryannis, A Brintrup International Journal of Production Research 62 (4), 1510-1540, 2024	6	2024
Digital twins: State of the art theory and practice, challenges, and open research questions. arXiv 2020 A Sharma, E Kosasih, J Zhang, A Brintrup, A Calinescu arXiv preprint arXiv:2011.02833, 0	5
Towards digital supply chain risk surveillance E Kosasih, A Brintrup IFAC-PapersOnLine 55 (10), 2499-2504, 2022	4	2022
Digital supply chain surveillance using artificial intelligence: definitions, opportunities and risks A Brintrup, E Kosasih, P Schaffer, G Zheng, G Demirel, BL MacCarthy International Journal of Production Research, 1-22, 2023	2	2023
Neurosymbolic Reasoning for Link Prediction in Supply Chain Knowledge Graphs E Kosasih		2023
GAETS: A Graph Autoencoder Time Series Approach Towards Battery Parameter Estimation EE Kosasih, RB Joshi, J Channegowda arXiv preprint arXiv:2111.09314, 2021		2021
Agrifood Data Study Group G Demirel

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